In today's society, users and organizations regularly utilize network and other service providers to gain access to the Internet, access software services, request and receive various types of content, access software applications, and perform a variety of other tasks and functions. As users and organizations have become comfortable with such technologies, an increasing number of such users and organizations have become accustomed to utilizing and interacting with cloud-based technologies to provide the services and content they desire. As a result, there has been an ever-increasing adoption of cloud-based deployments, which utilize a host of entities to provide the services and applications utilized by users and organizations. Such entities may include, but are not limited to, servers, virtual machines, hypervisors, tenants, switches, databases, other entities, or any combination thereof. In order to ensure that such entities are performing as expected, service providers have deployed network log analysis infrastructures to attempt to keep up with the processing demands of all the data generated from such entities. Such network log analysis infrastructures may be utilized to determine entity behaviors and to determine whether entities have been compromised, such as by malware.
While current network log analysis infrastructures provide for many benefits and efficiencies, current technologies still have many shortcomings. In particular, current network log analysis infrastructures are already struggling to keep up with the processing demands associated with processing the data generated from entities. Additionally, when the number of entities to monitor increases by a thousand-fold or million-fold, current network log analysis infrastructures will be unable to handle the processing demands that will occur as a result of such increases. Furthermore, current log analysis systems record network transaction events at specific network elements and then transport the logs associated with the events to a central processing system for processing. Such central processing systems often become overloaded with processing the data and significant delays in processing the data may result in long reaction times. As a result, current methodologies and technologies associated with processing data generated from entities may be modified so as to provide enhanced quality-of-service and to provide enhanced malware detection capabilities. Such enhancements and improvements to methodologies and technologies may provide for improved processing capabilities, increased security, and increased ease-of-use.